42 citations · 74 across the 11 of their papers we have counts for
11 papers
InfoChartQA: A Benchmark for Multimodal Question Answering on Infographic Charts
Tianchi Xie, Minzhi Lin, Mengchen Liu +3
Understanding infographic charts with design-driven visual elements (e.g., pictograms, icons) requires both visual recognition and reasoning, posing challenges for multimodal large…
ReorderBench: A Benchmark for Matrix Reordering
Jiangning Zhu, Zheng Wang, Zhiyang Shen +4
Matrix reordering permutes the rows and columns of a matrix to reveal meaningful visual patterns, such as blocks that represent clusters. A comprehensive collection of matrices, al…
Foundation Models Meet Visualizations: Challenges and Opportunities
Weikai Yang, Mengchen Liu, Zheng Wang +1
Recent studies have indicated that foundation models, such as BERT and GPT, excel in adapting to a variety of downstream tasks. This adaptability has established them as the domina…
Visual Analysis of Neural Architecture Spaces for Summarizing Design Principles
Jun Yuan, Mengchen Liu, Fengyuan Tian +1
Recent advances in artificial intelligence largely benefit from better neural network architectures. These architectures are a product of a costly process of trial-and-error. To ea…
A Survey of Visual Analytics Techniques for Machine Learning
Jun Yuan, Changjian Chen, Weikai Yang +3
Visual analytics for machine learning has recently evolved as one of the most exciting areas in the field of visualization. To better identify which research topics are promising a…
Diagnosing Concept Drift with Visual Analytics
Weikai Yang, Zhen Li, Mengchen Liu +4
Concept drift is a phenomenon in which the distribution of a data stream changes over time in unforeseen ways, causing prediction models built on historical data to become inaccura…
Analyzing the Noise Robustness of Deep Neural Networks
Kelei Cao, Mengchen Liu, Hang Su +3
Adversarial examples, generated by adding small but intentionally imperceptible perturbations to normal examples, can mislead deep neural networks (DNNs) to make incorrect predicti…
Analyzing the Noise Robustness of Deep Neural Networks
Mengchen Liu, Shixia Liu, Hang Su +2
Deep neural networks (DNNs) are vulnerable to maliciously generated adversarial examples. These examples are intentionally designed by making imperceptible perturbations and often…
Towards Better Analysis of Machine Learning Models: A Visual Analytics Perspective
Shixia Liu, Xiting Wang, Mengchen Liu +1
Interactive model analysis, the process of understanding, diagnosing, and refining a machine learning model with the help of interactive visualization, is very important for users…
Towards Better Analysis of Deep Convolutional Neural Networks
Mengchen Liu, Jiaxin Shi, Zhen Li +3
Deep convolutional neural networks (CNNs) have achieved breakthrough performance in many pattern recognition tasks such as image classification. However, the development of high-qu…
An Uncertainty-Aware Approach for Exploratory Microblog Retrieval
Mengchen Liu, Shixia Liu, Xizhou Zhu +3
Although there has been a great deal of interest in analyzing customer opinions and breaking news in microblogs, progress has been hampered by the lack of an effective mechanism to…